Synthetic Data for Insurance

Insurance companies have always been among the most data-savvy innovators, basically because the ability to calculate risks accurately makes or breaks their business. Nowadays, insurance companies around the world are engaging with artificial intelligence to build new data-driven capabilities and next-generation insurance products.

According to Gartner, as of 2022, analysts predict that 85% of algorithms used in the insurance industry will be incorrect because of bias. This is because in most cases, the datasets used to train AI models lack enough representation for women, people of color, and other minority groups. This underrepresentation not only affects insurers' business decisions but also consumers' lives, such as when customers in certain neighborhoods are charged higher premiums without a logical individual risk basis.

Challenges for AI in Insurance

Bias is just one of the many challenges that insurers encounter regarding the use of Artificial Intelligence:

1. Model Explainability

AI models are complex. Sometimes, even the data scientists who developed them do not know exactly how or why they work. This lack of explainability can prevent buy-in from business leaders, regulators, and customers. As regulatory pressure grows, explainable AI becomes a must-have.

2. Compliance

Insurers must adhere to multiple regulations, including data privacy rules such as GDPR and CCPA. Securing and maintaining regulatory compliance while using personal information for analytics is a constant struggle for the industry.

3. Achieving Business Value

Many AI models never reach production because of data sensitivity. Either teams are unable to access the data, or the data has been stripped of so much information (to protect privacy) that it is no longer useful for accurate training.

The Synthetic Data Solution

Synthetic data is emerging as a solution to all of these challenges. These datasets contain the same level of detail as original customer data but without the original personal details.

Synthetic data is quickly replacing traditional approaches like data masking, randomization, or generalization. This new approach is much more secure, saving money and accelerating AI model development since datasets can be created in a fraction of the time. Furthermore, model validation can be performed using high-quality AI-generated synthetic data, helping with interpretability methods like SHAP.

Use Cases for Insurers

Synthetic data can be generated in many shapes and forms. According to Gartner, by 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated. Here are the use cases with the highest ROI:

• 1. Model training / retraining: Creating optimized synthetic datasets enables maximum accuracy. Over time, AI models degrade; synthetic data allows for constant retraining and stability.
• 2. Risk assessment: Underwriting precision can be improved by providing accurate statistical insights or anonymizing metadata to model risk without exposing PII.
• 3. Fraud detection: Fraud detection systems can be strengthened by boosting incidences of fraud in the synthetic data, helping algorithms pick up rare patterns easier.
• 4. Eliminating bias: Skewness towards racial or gender bias can be corrected by generating additional records to compensate for biased training data.
• 5. Price optimization: Insurers can leverage geolocation data and synthetic addresses to make pricing models as accurate as if they were trained on real data, while staying compliant with HIPAA and CCPA.
• 6. Experience personalization: Develop and test new products that answer specific customer needs using data that complies with the strictest legal frameworks.

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Dedomena's platform allows insurance companies to boost their time-to-data and time-to-insight. By combining synthetic data generation with data enrichment, we unlock access to unlimited quality data for the entire AI development lifecycle. With advanced features like on-premise edge computation and complex data structure synthesis, Dedomena ensures better performance and faster deployment for the insurance sector.